CDP: The Evolution of Customer Data Platforms and Their Real Impact
Punyashloke Panigrahy
Senior Manager | Architect | Data Products | BFSI | Retail
How Data Strategies Complement Product Management to Drive Business Outcomes?
In today’s fast-paced digital landscape, many enterprises implement Customer 360 solutions or Customer Data Platforms (CDPs). While some professionals market CDPs as exclusive innovations or offer advice on governance and data quality, the reality is that the concept of CDPs isn’t new. In fact, nearly a decade ago, I led the implementation of a similar platform for HP Inc. using Salesforce in 2014-15.
So, what exactly is a CDP, and how does it drive business value?
What is a CDP?
A Customer Data Platform (CDP) is a versatile technology that enables businesses to unify customer information from multiple channels, systems, and data streams. Whether real-time or batch processing, a CDP builds a comprehensive customer profile, powering critical functions such as personalized marketing, insights, and targeted advertising.
Is a CDP a Data Product?
Absolutely. A CDP is fundamentally a data product. Its real power lies in enabling business outcomes like delivering “the right ads at the right time,” personalizing customer experiences, and generating actionable insights. However, to understand its full potential, we must explore how technology, data, and product management work together.
The Role of Data Strategies in CDP Success
Data strategies are the cornerstone of any CDP’s success. When aligned with product management, data strategies enhance customer experiences, streamline marketing efforts, and ultimately, drive business growth. Let’s dive deeper into one of the most critical features of a CDP: “the right ads at the right time.”
The Right Ads at the Right Time: Product Interest Score (PIS)
Through a CDP, organizations can target the ideal offer based on a customer’s past transactions and recent interactions, such as browsing or search behavior. But how do we achieve such precise targeting? The product interest score (PIS) is the engine behind this, which quantifies product engagement.
Calculating the Product Interest Score
The PIS is built around engagement metrics, commonly segmented under the AARRRE framework (Acquisition, Activation, Retention, Revenue, Referral, Engagement). Here’s a step-by-step approach to calculating the score:
1. Define Key Engagement Metrics:
2. Assign Weights to Each Action: Not all actions have equal significance. For instance:
3. Time Decay Factor: Recent actions generally carry more weight in determining interest:
4. Normalize the Score: To compare product interest across multiple customers or products, normalize the score within a specific range (e.g., 0-100).
5. Calculate the Interest Score: For each product, sum the weighted actions for each customer:
"Product Interest Score=∑(Action Weight×Frequency of Action)×Time Decay Factor"
6. Example Calculation: Let’s say a customer viewed a product five times, added it to their cart once, and clicked on a product email—all within the last 7 days:
7. Segment and Take Action: Once you’ve calculated PIS across customers and products, you can segment your audience based on interest levels and take action—whether it’s personalizing recommendations or prioritizing outreach.
Associating the PIS with the User Profile
Once calculated, the PIS is tied to an individual user’s profile within your system. The user profile includes:
With this data, you can create user segments (high, medium, low interest) and define targeted actions for each group.
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Leveraging Platforms for Personalized Ads
Based on a user’s PIS, you can leverage platforms like Facebook, Instagram, YouTube, and others to deliver personalized ads. Here’s how:
The User Journey Across Platforms
Monetizing CDP-Driven Insights
The power of a CDP extends far beyond targeted marketing. Here are several ways to monetize CDP data:
1. Performance-Based Advertising (CPA, CPC, CPM): Monetize ads through Cost Per Acquisition (CPA), Cost Per Click (CPC), or Cost Per Thousand Impressions (CPM). High PIS enables more precise targeting, improving click-through rates and generating higher ad revenue.
2. Retargeting and Remarketing: Retargeting campaigns can drive conversions for users who’ve interacted with a product but haven’t purchased it. Given a CDP's advanced segmentation capabilities, organizations can charge a premium for retargeted ads.
3. Subscription Models: Advertisers can pay for premium access to advanced targeting features powered by product interest scores. This can be part of a subscription or membership model offering more granular audience insights.
4. Affiliate Partnerships and Sponsored Content: Organizations can collaborate with affiliates to promote products through targeted ads, earning a commission for successful conversions.
5. Personalized Product Recommendations: Use PIS to deliver personalized product suggestions, increasing the average order value (AOV) through upselling or cross-selling opportunities.
6. Data Licensing: Monetize customer insights by licensing anonymized and aggregated data to third-party marketers or retailers who seek more accurate behavioral predictions.
7. A/B Testing and Optimization Fees: Offer advertisers data-driven insights to improve their campaigns. Charge for A/B testing services or ad optimization based on real-time customer data.
8. Exclusive Brand Partnerships: Use high PIS to form exclusive brand partnerships, offering tailored promotions that maximize conversion potential.
9. Increasing Lifetime Value (LTV): By keeping customers engaged with relevant ads, you increase their LTV, turning them into repeat buyers and brand advocates.
Technology Stack Powering CDP Success
The success of a CDP hinges on a solid data strategy that integrates various technologies, such as:
Conclusion: Data and Product Management – A Powerful Combination
In today’s data-driven landscape, CDPs aren’t just about storing and analyzing customer data. When data strategies are integrated into product management, they unlock the potential to drive tangible business outcomes. By aligning these strategies with cutting-edge technology, organizations can transform data products into commercial products—enabling growth, improving customer engagement, and maximizing revenue.
The Product Interest Score (PIS), in particular, personalizes the user journey by linking user interests to products and distributing targeted ads across platforms like Facebook, Instagram, and YouTube. This approach—based on real-time data and precise segmentation—ensures businesses can optimize their marketing efforts for better conversion rates and stronger customer relationships. The evidence is clear: leveraging PIS in alignment with technology platforms is a powerful strategy for any business looking to thrive in today’s competitive landscape.
By making the right strategic investments, organizations can maximize the value of their data, deepen customer connections, and set the stage for long-term success.
Note: The above technique is general (80%) and can be tailored or modified according to the organization’s needs. Opinions, feedback, and concerns are welcomed.
In part 2, we will discuss personalization soon.
Partial Credit: Salesforce.com 😊
Thought provoking article. Well done